A new superresolution technique is proposed for high-resolution estimation of the scattering analysis. For complicated multipath propagation environment, it is not enough to estimate only the delay-times of the signals. Some other information should be required to identify the signal path. The proposed method can estimate the frequency characteristic of each signal in addition to its delay-time. One method called modified (Root) MUSIC algorithm is known as a technique that can treat both of the parameters (frequency characteristic and delay-time). However, the method is based on some approximations in the signal decorrelation, that sometimes make problems. Therefore, further modification should be needed to apply the method to the complicated scattering analysis. In this paper, we propose to apply a time-domain null filtering scheme to reduce some of the dominant signal components. It can be shown by a simple experiment that the new technique can enhance estimation accuracy of the frequency characteristic in the Root-MUSIC algorithm.

A Q-band high gain and low noise Variable Gain Amplifier (VGA) module using dual gate AlGaAs/InGaAs pseudomorphic HEMTs has been developed. The dual gate HEMT can be fabricated by the same process of the single gate HEMT which has the gate length of 0.15 µm. The Q-band VGA module consists of a 1-stage low noise amplifier (LNA) MMIC using a single gate HEMT and a 2-stage VGA MMIC using dual gate HEMTs. During the design, an accurate noise modeling is introduced to achieve low noise performance. A fully passivated film is employed to achieve reliability. The VGA module has a gain of more than 20 dB from 41 GHz to 52 GHz and a maximum gain of 24.5 dB at 50 GHz. A gain control range of more than 30 dB is achieved in the same frequency range. A phase deviation is less than 10 degrees in 10 dB gain control range. A minimum noise figure of 1.8 dB with an associated gain of 22 dB is achieved at 43 GHz and the noise figure is less than 2.5 dB with associated gain of more than 20 dB from 41 GHz to 46 GHz when biased for low noise figure. This performance is comparable with the best data ever reported for LNAs at Q-band including both GaAs based HEMTs and InP based HEMTs.

In this paper, we present some contributions to improve a previous work's approach presented for the segmentation of magnetic resonance images of the human brain, based on the unsupervised Hopfield neural network. We formulate the segmentation problem as a minimization of an energy function constructed with two terms, the cost-term as a sum of errors' squares, and the second term is a temporary noise added to the cost-term as an excitation to the network to escape from certain local minimums and be more close to the global minimum. Also, to ensure the convergence of the network and its utility in clinic with useful results, the minimization is achieved with a step function permitting the network to reach its stability corresponding to a local minimum close to the global minimum in a prespecified period of time. We present here our approach segmentations results of a patient data diagnosed with a metastatic tumor in the brain, and we compare them to those obtained based on, previous works using Hopfield neural networks, Boltzmann machine and the conventional ISODATA clustering technique.

We define the Reallocation Problem to determine whether we can move products from their current store-houses to target storehouses in a number of moves which is less than or equal to a given number. This problem is defined simply and can be applied to many practical problems. We give necessary and sufficient conditions for feasibility for Reallocation Problems under various conditions, and propose liner time algorithms, when the volume of the products is restricted to 1. Moreover, we show that the Reallocation Problem is NP-complete in the strong sense, when the volume of the products is not restricted.

The recurrence method is useful for numerical calculation of the Bassel function Jv(x) of complex order v. The necessary total number of the recurrences in this method has been examined for the real order v, but it is known only for limited ranges of the real order v and the variable x, and it is not known for the complex order v. This letter proposes a new algorithm which increases the total number of the recurrences gradually, and which stops the calculation automatically when the approximate Bessel function with a necessary precision is obtained.

Digital halftoning is a well-known technique in image processing to convert an image having several bits for brightness levels into a binary image consisting only of black and white dots. A great number of algorithms have been presented for this problem, some of which have only been evaluated just by comparison with human eyes. In this paper we formulate the digital halftoning problem as a combinatiorial problem which allows an exact solution with graph-theoretic tools. For this, we consider a d-dimensional grid of n := Nd pixels (d 1). For each pixel, we define a so-called k-neighborhood, k {0,...N - 1}, which is the set of at most (2k + 1)d pixels that can be reached from the current pixel in a distance of k. Now, in order to solve the digital halftoning problem, we are going to minimize the sum of distances of all k-neighborhoods between the original picture and the halftoned one. We show that the problem can be solved in linear time in the one-dimensional case while it looks hopeless to have a polynomial-time algorithm in higher dimension including the usual two-dimensional case. We present an exact algorithm for the one-dimensional case which runs in O(n) time if k is regarded to be a constant. For two-dimensional case we present fast approximation techniques based on space filling curves. An experimental comparison of several implementations of approximate algorithms proves that our algorithms are of practical interest.

PID-type controllers have been well-known and widely used in many industries. Their regulation property of those was more improved through the addition of Bang-Bang-action. In spite of the potentials of these PID-plus Bang-Bang controllers, their regulation property is still limited by the fixed window limit value that determines the control action, i. e., PID or Bang-Bang. Thus, this paper presents an approach for improving the regulation property by dynamically changing the window limit value according to the plant dynamics with Neural Network predictive model. The improved regulation property is illustrated through simulation studies for position control of DC servo-motor system in the sense of classical figures of merit such as overshoot and rise time.

We present two efficient attribute evaluator construction methods for a wide subclass of L-attributed grammars by enumeration of attributed items during one-pass bottom-up parsing. We have already proposed a construction method of a parser/evaluator for the subclass of L-attributed grammar. However the evaluator produced by our previous method uses a great number of attributed items to evaluate all attributes of a given input string. In this paper we propose two generalized methods to reduce the number of attributed itmes used in attribute evaluation. Our methods allow us to evaluate all attributes taking advantage of the use of available lookahead information.

A novel method of multichannel surface EMG processing has been developed to compensate for the distortion in bipolar surface EMG signals due to the movement of innervation zones. The distortion of bipolar surface EMG signals was mathematically described as a filtering function. A compensating technique for such distorted bipolar surface EMG signals was developed for the brachial biceps during dynamic contractions in which the muscle length and tension change. The technique is based on multichannel surface EMG measurement, a method for estimating the movement of an innervation zone, and the inverse filtering technique. As a result, the distorted EMG signals were compensated and transformed into nearly identical waveforms, independent of the movement of the innervation zone.

In this paper, we give an algorithm which, given a set F of at most (n - 1) - k faulty nodes, and two sets S = {s1,..., sk} and T = {t1,..., tk}, 1 k n - 1, of nonfaulty nodes in n-dimensional star graphs Gn, finds k fault-free node disjoint paths si tji, where (j1,..., jk) is a permutation of (1,..., k), of length at most d(Gn) + 5 in O(kn) optimal time, where d(Gn) = 3(n-1)/2 is the diameter of Gn.

The Voronoi diagram is the most fundamental and useful concept in computational geometry. To understand impacts of non-Euclidean geometry on computational geometry, this paper investigates the Voronoi diagram in hyperbolic space. We first present characterizations of this diagram by means of the Enclidean Voronoi diagram, and based on them propose efficient algorithms to construct it. Some applications are also mentioned.

Discussed here is progress achieved in the development of video codec LSIs.First, the amount of computation for various standards, and signal handling capability (throughput) and power dissipation for video codec LSIs are described. Then, general technologies for improving throughtput are briefly summarized. The paper also reviews three approaches (i.e., video signal processor, building block and monolithic codes) for implementing video codes standards. The second half of the paper discusses various high-throughput technologies developed for programmable Video Signal Processor (VSP) LSIs. A number of VSP LSIs are introduced, including the world's first programmable VSP, developed in February 1987 and a monolithic codec ship, built in February 1993 that is sufficient in itself for the construction of a video encoder for encoding full-CIF data at 30 frames per second. Technologies for reduction of power dissipation while keeping maintaining throughput are also discussed.

This paper investigates some fundamental properties of alternating one-way (or two-way) pushdown automata (pda's) with sublogarithmic space. We first show that strongly (weakly) sublogarithmic space-bounded two-way alternating pda's are more powerful than one-way alternating pda's with the same space-bound. Then, we show that weakly sublogarithmic space-bounded two-way (one-way) alternating pda's are more powerful than two-way (one-way) nondeterministic pda's and alternating pda's with only universal states using the same space, and we also show that weakly sublogarithmic space-bounded one-way nondeterministic Turing machines are incomparable with one-way alternating Turing machines with only universal states using the same space. Furthermore, we investigate several fundamental closure properties, and show that the class of languages accepted by weakly sublogarithmic space-bounded one-way alternating pda's and the class of languages accepted by sublogarithmic space-bounded two-way deterministic pda's (nondeterministic pda's, alternating pda's with only universal states) are not closed under concatenation, Kleene closure, and length preserving homomorphism. Finally, we briefly investigate a relationship between 'strongly' and 'weakly'.

An ordered binary decision diagram (OBDD) is a directed acyclic graph for representing a Boolean function. OBDDs are widely used in various areas which require Boolean function manipulation, since they can represent efficiently many practical Boolean functions and have other desirable properties. However, there is very little theoretical research on the complexity of constructing an OBDD. In this paper, we prove that the optimal variable ordering problem of a shared BDD is NP-complete, and briefly discuss the approximation hardness of this problem and related OBDD problems.

Using fundamental device and circuits, we have realized three functions required for synaptic connections in self-organizing neural networks: long term memory of synaptic weights, fixed total amount of synaptic weights in a neuron, and lateral inhibition. The first two functions have been condensed into an optical adaptive device and circuits with floating gates. Lateral inhibition has been realized by a winner-take-all circuit and a following lateral excitatory connection circuit. We have fabricated these devices and circuits using CMOS technology and confirmed the three functions. In addition, topological mapping, which is essential for feature extraction, has been formed in a primitive network constructed with the fundamental device and circuits.

The base transit time of an Aluminum-graded-base PNp AlGaAs/GaAs heterojunction bipolar transistor (HBT) was studied in order to clarify the effect of aluminum grading in the base. Theoretical analysis using a classical drift diffusion model with velocity saturation at the base-collector junction and a high base quasielectric field (58 keV/cm) created by 20%-aluminum linear grading in a 400 base, leads to a base transit time (τb) of 0.9 ps. The base transit time is reduced by four times, compared to the base transit time of 3.6 ps without aluminum grading in the base. In order to demonstrate this advantage, we fabricated aluminum-graded-base PNp AlGaAs/GaAs heterojunction transistor which employs a 20%-aluminum linear graded 400 -wide base. The device with a 2 µm 10 µm emitter showed high RF performance with a cut-off frequency (ft) of 37 GHz and a maximum oscillation frequency (fmax) of 30 GHz at a collector current density of 3.4 104 A/cm2. Further analysis using direct parameter extraction of a small signal circuit model under the collector current density of 1.1-9.9104 A/cm2 indicated the intrinsic transit time, which is the sum of the base transit time and the collector depletion layer transit time (τSC), was as low as 2.3 ps under lowinjection level. Subtracting the collector depletion-layer transit time from the intrinsic time leads to a base transit time of 1.1 ps, which is close to the theoretical base transit time and is the shortest value ever reported. The structure is very attractive for pnp-type AlGaAs HBTs combined with Npn HBTs for complementary applications.

Recently, a number of concurrency control algorithms have been proposed for multidatabase system (MDBS) concurrency control methods (CCMs) and the most challenging issue of them has been a concern about how to ensure global serializability (GSR). In this paper, we examine two concurrency control algorithms of MDBS through simulation approach: optimistic ticket method (OTM) and global ticket method (GTM). In historical note, OTM is known to be the first practical solution, since this approach ensures GSR by way of automatically resolving indirect conflicts among global transactions without making any restrictions on local CCMs. However, OTM is expected to yield poor performance since it enforces all global transactions to take a local ticket which causes direct conflicts between them. In GTM, the global transaction manager in an MDBS assigns a global ticket to global transactions rather than accessing a local ticket as in OTM. Our experimental results showed that GTM outperforms OTM in cases that short timeout values are given. However, in case that the timeout value relatively becomes long, our results demonstrated that OTM outperforms GTM.

Optical switching networks to transport vast amounts of information are important for B-ISDN services. The wavelength division multiplexing (WDM) is emerging as the dominant technology for future optical networks. This paper proposes a large capacity photonic ATM switch architecture using WDM technology. The switch consists of two stages. The first stage is a space switch and the second stage is a wavelength switch. The proposed switch is suitable for WDM optical ATM networks, that is, an input and an output of the switch are wavelength-division-multiplexed. The switch can provide very large ATM cell switching capacity, for instance, 10Tbit/s, with reasonable complexity. The main switch module of the proposed switch has a simple architecture, and reduces the amount of a buffer hardware by introducing the WDM concept.

Among three factors mainly affecting the cache access time, i. e., hit access time, miss rate and miss penalty, previous approaches were focused on reducing the hit access time and miss rate. In this paper, we propose a scheme called MPC (Miss-Predicting Cache) which achives additional reduction of the average instruction cache access time through reducing the miss penalty. The MPC scheme which predicts cache miss and starts cache miss operations in advance, therefore, is supplementary to previous cache schemes targeted for reducing the miss rate and/or hit access time. Performance of the MPC scheme was evaluated using dinero, a trace-driven cache simulator, with the estimation of silicon area using 0.8 µm CMOS standard cell library.

We propose a new algorithm for minimizing the number of vertices of an approximate curve by keeping the error within a given bound (min-# problem) with the parallel-strip error criterion. The best existing algorithm which solves this problem has O (n2 log n) time complexity. Our algorithm which uses the Cone Intersection Method does not have an improved time complexity, but does have a high efficiency. In particular, for practical data such as those which represent the boundaries or the skeletons of an object, the new algorithm can solve the min-# problem in nearly O(n2) time.